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Interpretability

349 directly classified papers

Papers per year

Papers

Does Large Language Model Contain Task-Specific Neurons? EMNLP 2024
Latent Concept-based Explanation of NLP Models EMNLP 2024
Keep the Faith: Faithful Explanations in Convolutional Neural Networks for Case-Based Reasoning AAAI 2024
An L* Algorithm for Deterministic Weighted Regular Languages EMNLP 2024
G–LIME: Statistical Learning for Local Interpretations of Deep Neural Networks Using Global Priors (Abstract Reprint) AAAI 2024
Empowering CAM-Based Methods with Capability to Generate Fine-Grained and High-Faithfulness Explanations AAAI 2024
Generative Model for Decision Trees AAAI 2024
On the Universal Truthfulness Hyperplane Inside LLMs EMNLP 2024
Backward Lens: Projecting Language Model Gradients into the Vocabulary Space EMNLP 2024
Cluster-Norm for Unsupervised Probing of Knowledge EMNLP 2024
Robust Stochastic Graph Generator for Counterfactual Explanations AAAI 2024
Monotonic Representation of Numeric Attributes in Language Models ACL 2024
MCPNet: An Interpretable Classifier via Multi-Level Concept Prototypes CVPR 2024
Selective Explanations NIPS 2024
SLICE: Stabilized LIME for Consistent Explanations for Image Classification CVPR 2024
Brain Decodes Deep Nets CVPR 2024
MICA: Towards Explainable Skin Lesion Diagnosis via Multi-Level Image-Concept Alignment AAAI 2024
Stochastic Concept Bottleneck Models NIPS 2024
Towards General Robustness Verification of MaxPool-based Convolutional Neural Networks via Tightening Linear Approximation CVPR 2024
Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlation CVPR 2024
Identifying Important Group of Pixels using Interactions CVPR 2024
Interpretable Measures of Conceptual Similarity by Complexity-Constrained Descriptive Auto-Encoding CVPR 2024
Explaining the Implicit Neural Canvas: Connecting Pixels to Neurons by Tracing their Contributions CVPR 2024
Incremental Residual Concept Bottleneck Models CVPR 2024
Interactive Mars Image Content-Based Search with Interpretable Machine Learning AAAI 2024